Create custom reasoning patterns for AI agents with GraphRAG & knowledge ontology
Needs changesNeeds changes. This template uses 1 thing(s) that n8n 3.0 removes: AI Agent v1 (old agent modes). 1 breaking item(s) found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 5 nodes and runs when a chat message arrives. Along the way it connects OpenAI Chat Model and HTTP Request. It also calls infranodus.com over HTTP.
How it runs
Trigger: When a chat message arrives.
- Reasoning Agent (AI Agent): runs an AI agent, with model: OpenAI Chat Model; 1 tool (Interaction Dynamics Expert); memory: Simple Memory
Services it uses
HTTP calls to: infranodus.com
Before you upgrade to n8n 3.0
1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:
- AI Agent v1 (old agent modes) in Reasoning Agent (v1.9): replace with Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.
Rather not rewrite it? Many of these flows can be rebuilt in Make (free plan).
| Removed in 3.0 | Replace with |
|---|---|
| AI Agent v1 (old agent modes) Reasoning Agent (v1.9) | Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent. |
Nodes used (5)
- Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - Http Request Tool
n8n-nodes-base.httpRequestTool - AI Agent
@n8n/n8n-nodes-langchain.agent
From the author
Teach your AI agent HOW to think, not WHAT to think This workflow demonstrates how you can build an AI agent in n8n that uses the reasoning logic you define. So an LLM learns a way of thinking, which you can then apply to multiple problems: - Make an AI…